Cell division in deep material networks applied to multiscale strain localization modeling

Despite the increasing importance of strain localization modeling (e.g., failure analysis) in computer-aided engineering, there is a lack of effective approaches to capturing relevant material behaviors consistently across multiple length scales. We aim to address this gap within the framework of deep material networks (DMN) — a machine learning model with embedded mechanics in the building blocks. A new cell-division scheme is proposed to track...